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The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding (2406.02396v1)

Published 4 Jun 2024 in cs.CL and cs.AI

Abstract: The evaluation of English text embeddings has transitioned from evaluating a handful of datasets to broad coverage across many tasks through benchmarks such as MTEB. However, this is not the case for multilingual text embeddings due to a lack of available benchmarks. To address this problem, we introduce the Scandinavian Embedding Benchmark (SEB). SEB is a comprehensive framework that enables text embedding evaluation for Scandinavian languages across 24 tasks, 10 subtasks, and 4 task categories. Building on SEB, we evaluate more than 26 models, uncovering significant performance disparities between public and commercial solutions not previously captured by MTEB. We open-source SEB and integrate it with MTEB, thus bridging the text embedding evaluation gap for Scandinavian languages.

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Authors (4)
  1. Kenneth Enevoldsen (11 papers)
  2. Márton Kardos (7 papers)
  3. Niklas Muennighoff (56 papers)
  4. Kristoffer Laigaard Nielbo (3 papers)
Citations (6)